Making research valuable to communities: From social network analysis to engaged research

1. Making research valuable to
communities: From social network
analysis to engaged research
Mieke Bourne and Parmutia Makui

2. What is Social Network Analysis (SNA)?
• A tool to elicit, analyse and visualise social relations and networks
• Origins in sociology and mathematics (graph theory)
• Focus on structures and relationships rather than individual actor
attributes
• Show how actors interact, resources and information move and
structure of roles and responsibilities
• Actors (social entities) presented as nodes and the connections
between them as ties representing the relationship

3. Application of SNA
• Used in education, health, security etc
• Applied to agricultural systems in smallholder
farming communities recently:
– Vulnerability to climate change
– Technologies and resources
– Agriculture innovation processes

4. Process
• In workshop or FG setting discuss relationships between
relevant stakeholders/actors
• Participation at workshop/FG advised by key informants
and literature
• Opportunity for discussion and group understanding

5. Process
• Individuals (from stakeholder groups) fill in
questionnaire for quantitative results
• Questions on contacts, type, frequency,
quality, value and use
• Can also complete as survey using ODK

6. Data collection and preparation
• Data is either automatically collected using ODK
or entered in excel after collection
• Data for SNA is prepared in two different files:
– Nodes/Attributes data – had data people interviewed
e.g education, gender, social status etc
– Ties/Links data – has data on the relationships
observed e.g frequency of meeting etc
• This data can be prepared in excel spreadsheets.

7. Data analysis and visualization
• The analysis and visual maps to create would
depend on the objective to be investigated
• Analysis can be done using different software:
– UCINET and NetDraw
– R Statistical software and R Studio
– NodeXL
– Gephi
– Cytoscape
Some of the software are suited to handling data from
specific fields.

8. Resources
• Detailed descriptions of process can be found at:
Bourne M, Makui P, Muller A, Gassner A .2014. Social network analysis for determining gender-
differentiated sources of information and tree seedlings. In: ICRAF, 2014. Catacutan D, McGaw E &
Llanza MA (Eds). In Equal Measure: A User Guide to Gender Analysis in Agroforestry. Philippines.
Accessible at: http://www.worldagroforestry.org/publication/equal-measure-user-guide-gender-
analysis-agroforestry-0
• Description of some key network characteristics and measures:
Bourne, M., Gassner, A., Makui, P., Muller, A. & Muriuki, J. 2017. A network perspective filling a gap in
assessment of agricultural advisory system performance. Journal of Rural Studies, 50, 30-44.
• Guide to stakeholder mapping in the SAIRLA project:
Bourne M, Neely C, Winowiecki L, Hughes K. 2016. Guide to Stakeholder Mapping for the project:
Brining evidence to bear on negotiated ecosystem service and livelihood trade-offs in sustainable
agricultural intensification. World Agroforestry Centre, Kenya. Accessible at:
http://www.worldagroforestry.org/sites/default/files/outputs/Guide%20to%20stakeholder%20mapping
%202016_final%20uplodad%20for%202017.pdf

9. Seedling access by men and women in
Machakos, Kenya

11. Mwingi

13. Opportunities to extend the tool
• Present networks back to community as basis
for discussion – power of visualisation
• Have not done this for gender yet –move
beyond disaggregated data
• Capture social capital

14. Group discussion
• How can we extend this tool and in what
circumstances would it add value?
• How could this tool measure social capital?
5 minute discussion with your neighbour and
plenary sharing of thoughts

15. Thank you